On uncertainties in the reconstruction of nanostructures in EUV scatterometry and grazing incidence small-angle X-ray scattering

TL;DR

This paper explores the use of EUV scatterometry for non-destructive, high-throughput nanostructure characterization, demonstrating its advantages over GISAXS in probing smaller areas with lower divergence effects.

Contribution

It introduces a rigorous simulation and statistical validation approach for EUV scatterometry, enhancing nanostructure reconstruction accuracy and efficiency.

Findings

EUV scatterometry effectively characterizes nanostructures and oxide layers.

EUV allows probing smaller areas than GISAXS.

Lower divergence effects in EUV reduce computational effort.

Abstract

Increasing miniaturization and complexity of nanostructures require innovative metrology solutions with high throughput that can assess complex 3D structures in a non-destructive manner. EUV scatterometry is investigated for the characterization of nanostructured surfaces. The reconstruction is based on a rigorous simulation using a Maxwell solver based on finite-elements and is statistically validated with a Markov-Chain Monte Carlo sampling method. Here it is shown that this method is suitable for the dimensional characterization of the nanostructures and the investigation of oxide or contamination layers. In comparison to grazing-incidence small-angle X-rayscattering (GISAXS) EUV allows to probe smaller areas. The influence of the divergence on the diffracted intensities in EUV is much lower than in GISAXS, which also reduces the computational effort of the reconstruction.